Output Dinov3 Baseline

--- library_name: transformers license: other base_model: facebook/dinov3-vitb16-pretrain-lvd1689m tags: - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: output_dinov3_baseline results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # output_dinov3_baseline This model is a fine-tuned version of [facebook/dinov3-vitb16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vitb16-pretrain-lvd1689m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0561 - Precision: 0.9575 - Recall: 0.9706 - F1: 0.9640 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| | 0.4260 | 1.0 | 145 | 0.4096 | 0.5780 | 0.6891 | 0.6287 | | 0.2184 | 2.0 | 290 | 0.2185 | 0.8637 | 0.8519 | 0.8577 | | 0.1553 | 3.0 | 435 | 0.1501 | 0.8833 | 0.9307 | 0.9064 | | 0.1031 | 4.0 | 580 | 0.1093 | 0.9232 | 0.9601 | 0.9413 | | 0.0828 | 5.0 | 725 | 0.0866 | 0.9308 | 0.9748 | 0.9523 | | 0.0666 | 6.0 | 870 | 0.0746 | 0.9448 | 0.9716 | 0.9581 | | 0.0585 | 7.0 | 1015 | 0.0658 | 0.9652 | 0.9622 | 0.9637 | | 0.0500 | 8.0 | 1160 | 0.0613 | 0.9565 | 0.9695 | 0.9630 | | 0.0465 | 9.0 | 1305 | 0.0573 | 0.9584 | 0.9685 | 0.9634 | | 0.0420 | 10.0 | 1450 | 0.0561 | 0.9575 | 0.9706 | 0.9640 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.5.0 - Tokenizers 0.22.2

Source context: 13 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo buddhadeb33/output_dinov3_baseline

Source context: 5 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo buddhadeb33/output_dinov3_baseline